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It’s taken a while to cull through all the great entries we had for the March Photo Contest – thanks to all who submitted images. We’ve been treated to a wide array of distinctive and inventive 3D photographs during the last month! Without further ado, the winner of March’s contest is LudvikXIV for his submission of “Trojan Warrior IV”. Not only is this image incredibly creative, but the contrast of stylized background and the Trojan...
We’ve unlocked the capability on 3DVisionLive.com for anyone to upload their own 3D videos—previously you had to have your own channel and/or have your videos screened and approved by NVIDIA to upload them. We’re excited about this, and we hope you are too, as it will open the site to great deal of new content and, hopefully, community participation—both in terms of uploading videos and sharing and commenting on them. NOTE: We have added the ability...
We're proud to officially unveil the NVIDIA® GeForce® GTX 680, a next-generation GPU that delivers more than just state-of-the-art features and technology. It gives you truly game-changing performance that taps into the powerful next-generation GeForce architecture to redefine smooth, seamless, more realistic gaming. As 3D Vision users/fans the benefits of the new graphics architecture can be summed up in three main areas: Faster Innovative new...
And the Winner Is...   Our apologies for being a bit tardy in getting the results of the February photo contest posted - but good things come to those that wait... Without further ado, the winner is (cue drumroll please): "Warehouse in Wonderland", submitted by Nick Saglimbeni. We sure you'll agree that this shot features excellent composition and lighting control - as well as creative use of backlighting for a 3D subject. We also liked the...
3DVisionLive.com is excited to unveil the third in a series of monthly photo contests aimed at giving you a platform to show off your images and potentially win some cool prizes. The May Photo Contest is similar to April's and is open to legal residents of the United Kingdom, Germany, France, Norway, Sweden, Finland, Czech Republic, Russia, Australia, and the United States and Canada. Contest Rules The contest is open for submissions right now! So start...

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This April 22 put a little AI in your Earth Day.

Whether you’re cleaning up a beach, planting a tree or starting a garden, iNaturalist makes it easy to get in touch with nature.

iNaturalist is a crowd-sourced species identification app powered by AI. For the casual nature observer, the app allows people to snap photos of such easy targets as backyard plants and bugs and upload images for its AI to provide a match or for members of the community to identify.

The app is also a social network for nature enthusiasts to record information on species, meet others with similar interests and learn. It’s available on Android and iOS , where it’s already been downloaded nearly a million times.

It began as a website, iNaturalist.org, founded in 2008 by students at the University of California, Berkeley. Now it’s a joint program of the California Academy of Sciences and the National Geographic Society.

Previously it took 18 days on average for species to be identified by the website’s community. But that all changed after iNaturalist worked with researchers from Caltech and Cornell to build a computer vision AI into the app.

Now species can be identified in a matter of milliseconds, and much more accurately, with the use of AI, said Scott Loarie, co-director of iNaturalist.

“Our goal is to get millions of people outside exploring and connecting to nature and engage them to become lifelong stewards of the natural world,” Loarie said.

People mostly put up observations of plants to iNaturalist, but posts of birds, insects and other organisms can be found as well.

The app harnesses NVIDIA GPUs and the CUDA deep neural network library along with the TensorFlow deep learning framework, allowing training of the neural networks on a database of images that have been labeled by the site’s community of experts.

Today iNaturalist boasts 8.6 million observations uploaded and more than 155,000 species observed.

The post iNaturalist: An AI-Powered App to Crow About on Earth Day appeared first on The Official NVIDIA Blog.

Assessing risk is a concern in most industries, although perhaps never more so than following a merger or acquisition. It turns out AI may be just the tool to help.

GPU Technology Conference attendees last month got a high-level education in how AI can bring speed and precision to this process from Congruity360, a Massachusetts-based data management consultancy.

Mitigating Risk in M&A

Two people deciding to live together can see all of their belongings and make quick decisions about what to do with them. But a company that’s joined another is almost always saddled with data that’s not so easy to categorize.

While AI may not be well suited to analyzing text-based documents, Congruity360 has developed a method for parsing text data with GPU-powered machine learning.

“GPUs are not going to operate on text,” said Chris Ryan, vice president of sales engineering at Congruity360. “We need to come up with a mathematical representation of text documents.”

Doing so has allowed Congruity360 to classify unstructured documents based on whether they look the same or contain some of the same keywords. At its essence, the company’s work involves taking data it knows nothing about — “dark data,” as Ryan called it — and assigning high-level headers so it can separate the data into buckets related to topics such as invoices, taxes, intellectual property or even code.

The result is a visual representation that groups data in topical clusters, some of which stand on their own and some of which overlap. Companies can use this method to zero in on clusters of riskier documents, such as those that have regulatory implications.

Turning Data into Useful Information

Congruity360’s approach starts with the assumption that as much as 80 percent of all corporate data is unstructured, and seeks to answer the question, how can GPUs help machine learning turn raw text into information?

Most obviously, GPUs bring speed to the equation.

“If you’re a data scientist and you want to do this, you don’t want to wait weeks and weeks for models to run,” said Jonathan Bailey, vice president of analytics at Congruity360.

Speeding up the process translates to identifying — and mitigating — risks sooner. M&A activity involves working with legal teams, which are typically most concerned with ensuring that data is defensible. Congruity360 uses GPUs to perform comparisons of documents and compute their defensibility. It’s a process took four weeks using CPUs, and now unfolds in just 20 seconds on GPUs.

“We’re just trying to give users a tool to learn about data,” said Bailey. “We want to see if there’s any risky data in there.”

The post Risky Business: Tapping AI to Assess and Limit Risk in M&A appeared first on The Official NVIDIA Blog.